Publication in BibTeX Format

@TECHREPORT{AICPub600:1986,
AUTHOR={Pentland, Alex P.},
TITLE={Perceptual Organization and The Representation Of Natural Form},
ADDRESS={333 Ravenswood Ave., Menlo Park, CA 94025},
INSTITUTION={AI Center, SRI International},
MONTH={Jul},
NUMBER={357},
YEAR={1986},
KEYWORDS={Vision!Perceptual organization},
ABSTRACT={To support our reasoning abilities perception must recover environment
regularities–e.g., rigidity, ``objectness,’’ axes of symmetry–for
later use of cognition. To create a theory of how our perceptual apparatus
can produce meaningful cognitive primitives from an array of image intensities
we require a representation whose elements may be lawfully related to important
physical regularities, and that correctly describes the perceptual organization
people impose on the stimulus. Unfortunately, the representations that are
currently available were originally developed for other purposes (e.g., physics,
engineering) and have so far proven unsuitable for the problems of perception
or commonsense reasoning. In answer to this problem we present a representation
that has proven competent to accurately describe an extensive variety of natural
forms (e.g., people, mountains, clouds, trees), as well as man-made forms,
in a succinct and natural manner. The approach taken in this representational
system is to describe scene structure at a scale that is similar to our naive
perceptual notion of ``a part,’’ by use of descriptions that reflect
a possible formative history of the object, e.g., how the object might have
been constructed from lumps of clay. For this representation to be useful it
must be possible to recover such descriptions from image data; we show that
the primitive elements of such descriptions may be recovered in an overconstrained
and therefore reliable manner. We believe that this descriptive system makes
an important contribution towards solving current problems in perceiving and
reasoning about natural forms by allowing us to construct accurate descriptions
that are extremely compact and that capture people’s intuitive notions
about the part structure of three-dimensional forms.},
NOTE={Revised.}
}